Particle swarm optimization: Theory, literature review, and application in airfoil design

Seyedali Mirjalili, Jin Song Dong, Andrew Lewis, Ali Safa Sadiq

Research output: Chapter in Book/Report/Conference proceedingChapter

5 Citations (Scopus)

Abstract

The Particle Swarm Optimization (PSO) is one of the most well-regarded algorithms in the literature of meta-heuristics. This algorithm mimics the navigation and foraging behaviour of birds in nature. Despite the simple mathematical model, it has been widely used in diverse fields of studies to solve optimization problems. There is a tremendous number of theoretical works on this algorithm too that has led to a large number of variants, improvements, and hybrids. This chapter covers the inspirations, mathematical equations, and the main algorithm of this technique. Its performance is tested and analyzed on a challenging real-world problem in the field of aerospace engineering.

Original languageEnglish
Title of host publicationStudies in Computational Intelligence
PublisherSpringer Verlag
Pages167-184
Number of pages18
DOIs
Publication statusPublished - 1 Jan 2020
Externally publishedYes

Publication series

NameStudies in Computational Intelligence
Volume811
ISSN (Print)1860-949X

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Cite this

Mirjalili, S., Song Dong, J., Lewis, A., & Sadiq, A. S. (2020). Particle swarm optimization: Theory, literature review, and application in airfoil design. In Studies in Computational Intelligence (pp. 167-184). (Studies in Computational Intelligence; Vol. 811). Springer Verlag. https://doi.org/10.1007/978-3-030-12127-3_10